Chapter Two
Statistics and the
Research Process
The Logic of
Scientific Research
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Chapter 2 - 2
Scientific Research
• The goal of science is to understand the
“laws of nature”
• We examine a specific influence on a
specific behavior in a specific situation
• Then, we generalize back to the
broader behaviors and laws with which
we began.
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Chapter 2 - 3
Samples and
Populations
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Chapter 2 - 4
Samples and Populations
• The entire group to which a law applies
is the population
• A sample is a relatively small subset of
a population that is intended to
represent, or stand for, the population
• The individuals measured in a sample
are called the participants or subjects
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Chapter 2 - 5
Drawing Inferences
We use the scores in a sample to infer or
to estimate the scores we would expect to
find in the population.
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Chapter 2 - 6
Representativeness
In a representative sample, the
characteristics of the sample accurately
reflect the characteristics of the population.
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Chapter 2 - 7
Random Sampling
Random sampling is a method of
selecting a sample in which the
individuals are randomly selected from
the population.
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Chapter 2 - 8
Unrepresentative Samples
A random sample should be
representative of the population, but
never automatically assume that a sample
is representative of the population.
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Chapter 2 - 9
Obtaining Data
• A variable is anything that, when measured,
can produce two or more different values.
Some common variables are:
– Age
– Race
– Gender
– Intelligence
– Personality type
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Chapter 2 - 10
Types of Variables
• A quantitative variable indicates the
amount of a variable that is present
• A qualitative variable classifies an
individual on the basis of some
characteristic
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Chapter 2 - 11
Examining Relationships
A relationship occurs when a change in
one variable is accompanied by a
consistent change in another variable.
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Chapter 2 - 12
Strength of a Relationship
• The strength of a relationship is the
extent to which one value of Y is
consistently associated with one and
only one value of X.
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Chapter 2 - 13
Factors Affecting Strength
• A “weaker” relationship may be due to
additional extraneous influences and/or
individual differences
• Individual differences refer to the fact
that no two individuals are identical
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Chapter 2 - 14
Graphing Relationships
• Describe a relationship using the
general format:
– “Scores on the Y variable change as a
function of changes in the X variable.”
– The given variable in a study is the X
variable.
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Chapter 2 - 15
Four Sample Graphs
A graph
showing
a perfectly
consistent
association.
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Chapter 2 - 16
Four Sample Graphs
A relationship
that is not
perfectly
consistent.
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Chapter 2 - 17
Four Sample Graphs
A weak
relationship.
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[Insert new Figure 2.1,
Graph C here.]
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Four Sample Graphs
No consistent
pattern.
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[Insert new Figure 2.1,
Graph D here.]
Chapter 2 - 19
Applying Descriptive and
Inferential Statistics
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Chapter 2 - 20
Descriptive Statistics
• Descriptive statistics are procedures
used for organizing and summarizing
data.
– What scores occurred?
– What’s the average or typical score?
– Are the scores very similar to each other or very different
and spread out?
– Is a relationship present?
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Chapter 2 - 21
Inferential Statistics
• Inferential statistics are procedures for
deciding whether sample data
accurately represent a particular
relationship in the population
• Inferential statistics allow us to make
inferences about the score and
relationship found in the population
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Chapter 2 - 22
Statistics and Parameters
• A statistic is a number that describes a
characteristic of a sample of scores
• A parameter is a number that describes
a characteristic of a population of
scores
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Chapter 2 - 23
Understanding Experiments and
Correlational Studies
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Chapter 2 - 24
Research Designs
• A study’s design is the way the study is
laid out.
• There are two major types of designs:
– Experiments
– Correlational studies
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Chapter 2 - 25
Experiments
In an experiment the researcher actively
changes or manipulates one variable and
then measures participants’ scores on
another variable to see if a relationship is
produced
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Chapter 2 - 26
The Independent Variable
• The independent variable is the
variable that is changed or manipulated
by the experimenter.
• A condition is a specific amount or
category of the independent variable
that creates the specific situation under
which participants’ scores on another
variable are measured.
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Chapter 2 - 27
The Dependent Variable
The dependent variable is the variable
that is measured under each condition of
the independent variable.
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Chapter 2 - 28
Correlational Studies
• In a correlational study, we simply
measure participants’ scores on two
variables and then determine whether a
relationship is present
• We can never conclude that changes in
one variable cause the other variable to
change based on a correlational study
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Chapter 2 - 29
Causality
We cannot definitively prove that the
independent variable causes the scores
on the dependent variable to change. It is
always possible that some other hidden
variable is actually the cause.
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Chapter 2 - 30
The Characteristics
of the Scores
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Chapter 2 - 31
Characteristics of Variables
• Two important characteristics of
variables are
– The type of measurement scale involved
– Whether it is continuous or discrete
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Chapter 2 - 32
Measurement Scales
• There are four types of measurement
scales:
– A nominal scale does not indicate an
amount; rather, it is used for identification,
as a name.
– An ordinal scale indicates rank order.
There is not an equal unit of measurement
separating each score.
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Chapter 2 - 33
Measurement Scales (cont’d)
– An interval scale indicates an actual
quantity and there is an equal unit of
measurement separating adjacent scores.
Interval scales do not have a “true” 0.
– A ratio scale reflects the true amount of
the variable that is present because the
scores measure an actual amount, there is
an equal unit of measurement, and 0 truly
means that zero amount of the variable is
present.
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Chapter 2 - 34
Discrete and Continuous
• Any measurement scale also may be
either continuous or discrete
• A continuous scale allows for
fractional amounts and so decimals
make sense
• In a discrete scale, only whole-number
amounts can be measured
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Chapter 2 - 35
Summary of
Measurement Scales
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Chapter 2 - 36